Big Data: A Tool for Inclusion or Exclusion?, Understanding the Issues | Federal Trade Commission (FTC)

Big Data: A Tool for Inclusion or Exclusion?, Understanding the Issues; Federal Trade Commission (FTC); 2016-01-06; 50 pages; landing.

Authors
at the Federal Trade Commission (FTC)

  • Edith Ramirez, Chairwoman
  • Julie Brill, Commissioner
  • Maureen K. Ohlhausen, Commissioner
  • Terrell McSweeny, Commissioner

Mentions

  • Followup from the workshop 2014-09-25 (some fifteen months prior).
  • Big Data is
    •  … (wait for it) … very big.
    • created out of Little data by the process
      1. collection
      2. compilation & consolidation
      3. analysis
      4. use
    • The Three ‘V’s, a framework
      1. volume
      2. velocity
      3. variety
      4. veracity [the fourth]
  • Regulatory interest occurs at Step (4), Use.
  • Regulations
    • Fair Credit Reporting Act (FCRA)
    • Equal Credit Opportunity Act (ECOA)
      • Regulation B
    • Americans with Disabilities Act (ADA)
    • Age Discrimination in Employment Act (ADEA)
    • Fair Housing Act (FHA)
    • Genetic Information Nondiscrimination Act (GINA)
    • Federal Trade Commission Act (FTC Act)
  • Theories, Devices, (Bright-Line) Tests
    • disparate treatment
    • disparate impact, (unjustified) disparate impact
    • protected class
    • deceptive practices
    • unfair practices
  • Categories
    • Data Broker
    • low-income
    • underserved populations
    • protected groups, protected class
  • <quote>if a company has a big data algorithm that only considers applicants from “top tier” colleges to help them make hiring decisions, they may be incorporating previous biases in college admission decision</quote>, page iv (page 12)

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